Overview

Brought to you by YData

Dataset statistics

Number of variables	26
Number of observations	148
Missing cells	738
Missing cells (%)	19.2%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	123.0 KiB
Average record size in memory	851.4 B

Variable types

Text	2
DateTime	1
Categorical	14
Numeric	8
Unsupported	1

Alerts

`cant_suspensiones` has constant value "1.0"	Constant
`cant_antecedentes` has constant value "1.0"	Constant
`Cluster_6` has constant value "4"	Constant
`anio_preinscripcion` is highly overall correlated with `antiguedad` and 1 other fields	High correlation
`antiguedad` is highly overall correlated with `anio_preinscripcion` and 1 other fields	High correlation
`cant_Apoderado` is highly overall correlated with `cant_MontoLimite` and 2 other fields	High correlation
`cant_MontoLimite` is highly overall correlated with `cant_Apoderado` and 2 other fields	High correlation
`cant_autenticado` is highly overall correlated with `cant_Apoderado` and 1 other fields	High correlation
`cant_noAutenticado` is highly overall correlated with `cant_Apoderado` and 2 other fields	High correlation
`cant_procesos_adjudicado` is highly overall correlated with `dcant_procesos_adjudicado` and 1 other fields	High correlation
`cant_representante` is highly overall correlated with `monto_total_adjudicado`	High correlation
`cant_socios` is highly overall correlated with `cant_noAutenticado`	High correlation
`dcant_procesos_adjudicado` is highly overall correlated with `cant_procesos_adjudicado`	High correlation
`dtotal_articulos_provee` is highly overall correlated with `total_articulos_provee`	High correlation
`monto_total_adjudicado` is highly overall correlated with `cant_procesos_adjudicado` and 1 other fields	High correlation
`periodo_preinscripcion` is highly overall correlated with `anio_preinscripcion` and 1 other fields	High correlation
`provincia` is highly overall correlated with `total_articulos_provee`	High correlation
`total_articulos_provee` is highly overall correlated with `dtotal_articulos_provee` and 1 other fields	High correlation
`cant_representante` is highly imbalanced (58.2%)	Imbalance
`cant_MontoLimite` is highly imbalanced (61.0%)	Imbalance
`cant_socios` has 8 (5.4%) missing values	Missing
`cant_apercibimientos` has 148 (100.0%) missing values	Missing
`cant_suspensiones` has 147 (99.3%) missing values	Missing
`cant_antecedentes` has 147 (99.3%) missing values	Missing
`cant_Apoderado` has 41 (27.7%) missing values	Missing
`cant_representante` has 60 (40.5%) missing values	Missing
`cant_noAutenticado` has 102 (68.9%) missing values	Missing
`cant_sinMontoLimite` has 85 (57.4%) missing values	Missing
`CUIT` has unique values	Unique
`Nombre` has unique values	Unique
`cant_apercibimientos` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`monto_total_adjudicado` has 2 (1.4%) zeros	Zeros
`antiguedad` has 8 (5.4%) zeros	Zeros

Reproduction

Analysis started	2025-06-30 18:10:12.124865
Analysis finished	2025-06-30 18:10:19.679709
Duration	7.55 seconds
Software version	ydata-profiling vv4.16.1
Download configuration	config.json

CUIT
Text

Unique

Distinct	148
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	11.0 KiB

Length

Max length	13
Median length	11
Mean length	10.986486
Min length	9

Characters and Unicode

Total characters	1626
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	148 ?
Unique (%)	100.0%

Sample

1st row	30558766987
2nd row	30715168800
3rd row	30664177818
4th row	30620477113
5th row	30629086524

Value	Count	Frequency (%)
30558766987	1	0.7%
30715168800	1	0.7%
30664177818	1	0.7%
30620477113	1	0.7%
30629086524	1	0.7%
33708630409	1	0.7%
30525366657	1	0.7%
30505725774	1	0.7%
30710910916	1	0.7%
30696184263	1	0.7%
Other values (138)	138	93.2%

Most occurring characters

Value	Count	Frequency (%)
0	282	17.3%
3	263	16.2%
7	185	11.4%
1	162	10.0%
6	155	9.5%
8	130	8.0%
4	124	7.6%
2	115	7.1%
5	112	6.9%
9	95	5.8%
Other values (3)	3	0.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1626	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	282	17.3%
3	263	16.2%
7	185	11.4%
1	162	10.0%
6	155	9.5%
8	130	8.0%
4	124	7.6%
2	115	7.1%
5	112	6.9%
9	95	5.8%
Other values (3)	3	0.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1626	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	282	17.3%
3	263	16.2%
7	185	11.4%
1	162	10.0%
6	155	9.5%
8	130	8.0%
4	124	7.6%
2	115	7.1%
5	112	6.9%
9	95	5.8%
Other values (3)	3	0.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1626	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	282	17.3%
3	263	16.2%
7	185	11.4%
1	162	10.0%
6	155	9.5%
8	130	8.0%
4	124	7.6%
2	115	7.1%
5	112	6.9%
9	95	5.8%
Other values (3)	3	0.2%

Nombre
Text

Unique

Distinct	148
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	12.9 KiB

Length

Max length	82
Median length	39
Mean length	20.364865
Min length	6

Characters and Unicode

Total characters	3014
Distinct characters	66
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	148 ?
Unique (%)	100.0%

Sample

1st row	EDITORIAL ALBATROS
2nd row	construir futuros
3rd row	FUNDACION DE LA UNIVERSIDAD NACIONAL DEL SUR
4th row	MULTICABLE S.A.
5th row	AD-HOC S.R.L.

Value	Count	Frequency (%)
s.a	37	7.9%
srl	31	6.6%
s.r.l	27	5.7%
de	19	4.0%
sa	17	3.6%
la	9	1.9%
y	7	1.5%
argentina	6	1.3%
s.a.s	4	0.9%
group	4	0.9%
Other values (287)	309	65.7%

Most occurring characters

Value	Count	Frequency (%)
	322	10.7%
A	232	7.7%
S	231	7.7%
R	180	6.0%
.	166	5.5%
E	137	4.5%
O	136	4.5%
L	134	4.4%
I	128	4.2%
N	97	3.2%
Other values (56)	1251	41.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3014	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	322	10.7%
A	232	7.7%
S	231	7.7%
R	180	6.0%
.	166	5.5%
E	137	4.5%
O	136	4.5%
L	134	4.4%
I	128	4.2%
N	97	3.2%
Other values (56)	1251	41.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3014	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	322	10.7%
A	232	7.7%
S	231	7.7%
R	180	6.0%
.	166	5.5%
E	137	4.5%
O	136	4.5%
L	134	4.4%
I	128	4.2%
N	97	3.2%
Other values (56)	1251	41.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3014	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	322	10.7%
A	232	7.7%
S	231	7.7%
R	180	6.0%
.	166	5.5%
E	137	4.5%
O	136	4.5%
L	134	4.4%
I	128	4.2%
N	97	3.2%
Other values (56)	1251	41.5%

FechaPreinscripcion
Date

Distinct	120
Distinct (%)	81.1%
Missing	0
Missing (%)	0.0%
Memory size	2.3 KiB

Minimum	2016-01-11 00:00:00
Maximum	2022-09-05 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

Estado
Categorical

Distinct	5
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Memory size	11.6 KiB

Inscripto	110
Desactualizado doc. vencidos	25
Desactualizado mantención	7
Pre Inscripto	5
En Evaluacion	1

Length

Max length	28
Median length	9
Mean length	13.128378
Min length	9

Characters and Unicode

Total characters	1943
Distinct characters	23
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.7%

Sample

1st row	Inscripto
2nd row	Desactualizado doc. vencidos
3rd row	Desactualizado doc. vencidos
4th row	Inscripto
5th row	Desactualizado doc. vencidos

Common Values

Value	Count	Frequency (%)
Inscripto	110	74.3%
Desactualizado doc. vencidos	25	16.9%
Desactualizado mantención	7	4.7%
Pre Inscripto	5	3.4%
En Evaluacion	1	0.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
inscripto	115	54.5%
desactualizado	32	15.2%
doc	25	11.8%
vencidos	25	11.8%
mantención	7	3.3%
pre	5	2.4%
en	1	0.5%
evaluacion	1	0.5%

Most occurring characters

Value	Count	Frequency (%)
c	205	10.6%
o	198	10.2%
i	180	9.3%
s	172	8.9%
n	163	8.4%
t	154	7.9%
r	120	6.2%
p	115	5.9%
I	115	5.9%
a	105	5.4%
Other values (13)	416	21.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1943	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
c	205	10.6%
o	198	10.2%
i	180	9.3%
s	172	8.9%
n	163	8.4%
t	154	7.9%
r	120	6.2%
p	115	5.9%
I	115	5.9%
a	105	5.4%
Other values (13)	416	21.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1943	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
c	205	10.6%
o	198	10.2%
i	180	9.3%
s	172	8.9%
n	163	8.4%
t	154	7.9%
r	120	6.2%
p	115	5.9%
I	115	5.9%
a	105	5.4%
Other values (13)	416	21.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1943	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
c	205	10.6%
o	198	10.2%
i	180	9.3%
s	172	8.9%
n	163	8.4%
t	154	7.9%
r	120	6.2%
p	115	5.9%
I	115	5.9%
a	105	5.4%
Other values (13)	416	21.4%

TipoSocietario
Categorical

Distinct	8
Distinct (%)	5.4%
Missing	0
Missing (%)	0.0%
Memory size	13.7 KiB

S.R.L	61
Sociedad Anónima	58
Otras Formas Societarias	10
Persona Física	5
Sociedades De Hecho	4
Other values (3)	10

Length

Max length	26
Median length	24
Mean length	12.135135
Min length	5

Characters and Unicode

Total characters	1796
Distinct characters	36
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Sociedad Anónima
2nd row	Sociedades De Hecho
3rd row	Otras Formas Societarias
4th row	Sociedad Anónima
5th row	S.R.L

Common Values

Value	Count	Frequency (%)
S.R.L	61	41.2%
Sociedad Anónima	58	39.2%
Otras Formas Societarias	10	6.8%
Persona Física	5	3.4%
Sociedades De Hecho	4	2.7%
Cooperativas	4	2.7%
Organismo Publico	3	2.0%
PJ Extranjero Sin Sucursal	3	2.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
s.r.l	61	24.3%
sociedad	58	23.1%
anónima	58	23.1%
otras	10	4.0%
formas	10	4.0%
societarias	10	4.0%
persona	5	2.0%
física	5	2.0%
sociedades	4	1.6%
de	4	1.6%
Other values (8)	26	10.4%

Most occurring characters

Value	Count	Frequency (%)
a	187	10.4%
i	158	8.8%
S	139	7.7%
n	130	7.2%
d	124	6.9%
.	122	6.8%
o	108	6.0%
	103	5.7%
e	96	5.3%
c	87	4.8%
Other values (26)	542	30.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1796	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	187	10.4%
i	158	8.8%
S	139	7.7%
n	130	7.2%
d	124	6.9%
.	122	6.8%
o	108	6.0%
	103	5.7%
e	96	5.3%
c	87	4.8%
Other values (26)	542	30.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1796	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	187	10.4%
i	158	8.8%
S	139	7.7%
n	130	7.2%
d	124	6.9%
.	122	6.8%
o	108	6.0%
	103	5.7%
e	96	5.3%
c	87	4.8%
Other values (26)	542	30.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1796	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	187	10.4%
i	158	8.8%
S	139	7.7%
n	130	7.2%
d	124	6.9%
.	122	6.8%
o	108	6.0%
	103	5.7%
e	96	5.3%
c	87	4.8%
Other values (26)	542	30.2%

periodo_preinscripcion
Real number (ℝ)

High correlation

Distinct	42
Distinct (%)	28.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	201728.48

Minimum	201607
Maximum	202209
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.3 KiB

Quantile statistics

Minimum	201607
5-th percentile	201610.35
Q1	201612
median	201703
Q3	201708
95-th percentile	202074.05
Maximum	202209
Range	602
Interquartile range (IQR)	96

Descriptive statistics

Standard deviation	135.65339
Coefficient of variation (CV)	0.00067245534
Kurtosis	4.4471404
Mean	201728.48
Median Absolute Deviation (MAD)	6.5
Skewness	2.1099114
Sum	29855815
Variance	18401.843
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=42)

Value	Count	Frequency (%)
201611	23	15.5%
201704	17	11.5%
201701	16	10.8%
201702	13	8.8%
201703	9	6.1%
201612	8	5.4%
201705	7	4.7%
201610	5	3.4%
201707	4	2.7%
201706	4	2.7%
Other values (32)	42	28.4%

Value	Count	Frequency (%)
201607	2	1.4%
201609	1	0.7%
201610	5	3.4%
201611	23	15.5%
201612	8	5.4%
201701	16	10.8%
201702	13	8.8%
201703	9	6.1%
201704	17	11.5%
201705	7	4.7%

Value	Count	Frequency (%)
202209	1	0.7%
202206	1	0.7%
202205	1	0.7%
202204	1	0.7%
202203	1	0.7%
202110	1	0.7%
202109	1	0.7%
202108	1	0.7%
202011	1	0.7%
202008	1	0.7%

anio_preinscripcion
Real number (ℝ)

High correlation

Distinct	7
Distinct (%)	4.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2017.223

Minimum	2016
Maximum	2022
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.3 KiB

Quantile statistics

Minimum	2016
5-th percentile	2016
Q1	2016
median	2017
Q3	2017
95-th percentile	2020.65
Maximum	2022
Range	6
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.3643715
Coefficient of variation (CV)	0.00067636125
Kurtosis	4.2877704
Mean	2017.223
Median Absolute Deviation (MAD)	0
Skewness	2.0480778
Sum	298549
Variance	1.8615095
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
2017	79	53.4%
2016	39	26.4%
2018	13	8.8%
2019	5	3.4%
2022	5	3.4%
2020	4	2.7%
2021	3	2.0%

Value	Count	Frequency (%)
2016	39	26.4%
2017	79	53.4%
2018	13	8.8%
2019	5	3.4%
2020	4	2.7%
2021	3	2.0%
2022	5	3.4%

Value	Count	Frequency (%)
2022	5	3.4%
2021	3	2.0%
2020	4	2.7%
2019	5	3.4%
2018	13	8.8%
2017	79	53.4%
2016	39	26.4%

cant_procesos_adjudicado
Real number (ℝ)

High correlation

Distinct	29
Distinct (%)	19.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	8.9256757

Minimum	1
Maximum	209
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.3 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	8
95-th percentile	34.5
Maximum	209
Range	208
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	21.252
Coefficient of variation (CV)	2.3809962
Kurtosis	55.420026
Mean	8.9256757
Median Absolute Deviation (MAD)	1
Skewness	6.5957409
Sum	1321
Variance	451.6475
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
1	55	37.2%
2	22	14.9%
3	11	7.4%
6	8	5.4%
4	7	4.7%
5	5	3.4%
12	4	2.7%
9	3	2.0%
17	3	2.0%
8	3	2.0%
Other values (19)	27	18.2%

Value	Count	Frequency (%)
1	55	37.2%
2	22	14.9%
3	11	7.4%
4	7	4.7%
5	5	3.4%
6	8	5.4%
7	1	0.7%
8	3	2.0%
9	3	2.0%
10	2	1.4%

Value	Count	Frequency (%)
209	1	0.7%
91	1	0.7%
78	1	0.7%
57	1	0.7%
51	1	0.7%
45	1	0.7%
43	1	0.7%
38	1	0.7%
28	1	0.7%
26	1	0.7%

monto_total_adjudicado
Real number (ℝ)

High correlation Zeros

Distinct	147
Distinct (%)	99.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	58533588

Minimum	0
Maximum	1.9100989 × 10⁹
Zeros	2
Zeros (%)	1.4%
Negative	0
Negative (%)	0.0%
Memory size	2.3 KiB

Quantile statistics

Minimum	0
5-th percentile	44560.921
Q1	501709.89
median	4552040
Q3	24238704
95-th percentile	2.523927 × 10⁸
Maximum	1.9100989 × 10⁹
Range	1.9100989 × 10⁹
Interquartile range (IQR)	23736994

Descriptive statistics

Standard deviation	2.126799 × 10⁸
Coefficient of variation (CV)	3.6334677
Kurtosis	50.783806
Mean	58533588
Median Absolute Deviation (MAD)	4422417.6
Skewness	6.7416776
Sum	8.6629711 × 10⁹
Variance	4.5232742 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2	1.4%
139515.1613	1	0.7%
47514199	1	0.7%
897332.6613	1	0.7%
13718355.26	1	0.7%
129531720.6	1	0.7%
43707	1	0.7%
4155352.146	1	0.7%
153227947.9	1	0.7%
1135621.435	1	0.7%
Other values (137)	137	92.6%

Value	Count	Frequency (%)
0	2	1.4%
0.01	1	0.7%
1912.5	1	0.7%
16790.76923	1	0.7%
29527.62	1	0.7%
36000	1	0.7%
43707	1	0.7%
46146.77419	1	0.7%
53580	1	0.7%
67961.6129	1	0.7%

Value	Count	Frequency (%)
1910098932	1	0.7%
1418191729	1	0.7%
825396407.4	1	0.7%
367857550.6	1	0.7%
341587058.6	1	0.7%
335474338.9	1	0.7%
321925562.7	1	0.7%
255189952.4	1	0.7%
247197792.1	1	0.7%
176746834.4	1	0.7%

antiguedad
Real number (ℝ)

High correlation Zeros

Distinct	6
Distinct (%)	4.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.8108108

Minimum	0
Maximum	5
Zeros	8
Zeros (%)	5.4%
Negative	0
Negative (%)	0.0%
Memory size	2.3 KiB

Quantile statistics

Minimum	0
5-th percentile	0.35
Q1	4
median	4
Q3	5
95-th percentile	5
Maximum	5
Range	5
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.2527594
Coefficient of variation (CV)	0.32873829
Kurtosis	2.9056252
Mean	3.8108108
Median Absolute Deviation (MAD)	0
Skewness	-1.7609328
Sum	564
Variance	1.5694061
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
4	79	53.4%
5	39	26.4%
3	13	8.8%
0	8	5.4%
2	5	3.4%
1	4	2.7%

Value	Count	Frequency (%)
0	8	5.4%
1	4	2.7%
2	5	3.4%
3	13	8.8%
4	79	53.4%
5	39	26.4%

Value	Count	Frequency (%)
5	39	26.4%
4	79	53.4%
3	13	8.8%
2	5	3.4%
1	4	2.7%
0	8	5.4%

provincia
Categorical

High correlation

Distinct	19
Distinct (%)	12.8%
Missing	0
Missing (%)	0.0%
Memory size	10.8 KiB

CABA	83
Buenos Aires	23
Córdoba	13
Santa Fe	5
San Luis	4
Other values (14)	20

Length

Max length	16
Median length	4
Mean length	6.3851351
Min length	4

Characters and Unicode

Total characters	945
Distinct characters	38
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	10 ?
Unique (%)	6.8%

Sample

1st row	CABA
2nd row	Buenos Aires
3rd row	Buenos Aires
4th row	CABA
5th row	CABA

Common Values

Value	Count	Frequency (%)
CABA	83	56.1%
Buenos Aires	23	15.5%
Córdoba	13	8.8%
Santa Fe	5	3.4%
San Luis	4	2.7%
Rio Negro	3	2.0%
Extranjera	3	2.0%
La Pampa	2	1.4%
Tucumán	2	1.4%
Neuquén	1	0.7%
Other values (9)	9	6.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
caba	83	43.7%
buenos	23	12.1%
aires	23	12.1%
córdoba	13	6.8%
santa	6	3.2%
fe	5	2.6%
san	5	2.6%
luis	4	2.1%
rio	3	1.6%
negro	3	1.6%
Other values (17)	22	11.6%

Most occurring characters

Value	Count	Frequency (%)
A	189	20.0%
B	106	11.2%
C	100	10.6%
e	66	7.0%
s	54	5.7%
r	51	5.4%
o	48	5.1%
a	46	4.9%
n	45	4.8%
	42	4.4%
Other values (28)	198	21.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	945	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
A	189	20.0%
B	106	11.2%
C	100	10.6%
e	66	7.0%
s	54	5.7%
r	51	5.4%
o	48	5.1%
a	46	4.9%
n	45	4.8%
	42	4.4%
Other values (28)	198	21.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	945	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
A	189	20.0%
B	106	11.2%
C	100	10.6%
e	66	7.0%
s	54	5.7%
r	51	5.4%
o	48	5.1%
a	46	4.9%
n	45	4.8%
	42	4.4%
Other values (28)	198	21.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	945	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
A	189	20.0%
B	106	11.2%
C	100	10.6%
e	66	7.0%
s	54	5.7%
r	51	5.4%
o	48	5.1%
a	46	4.9%
n	45	4.8%
	42	4.4%
Other values (28)	198	21.0%

cant_socios
Real number (ℝ)

High correlation Missing

Distinct	9
Distinct (%)	6.4%
Missing	8
Missing (%)	5.4%
Infinite	0
Infinite (%)	0.0%
Mean	2.2714286

Minimum	1
Maximum	18
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.3 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	3
95-th percentile	5
Maximum	18
Range	17
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.9813623
Coefficient of variation (CV)	0.87229786
Kurtosis	31.748461
Mean	2.2714286
Median Absolute Deviation (MAD)	1
Skewness	4.8293037
Sum	318
Variance	3.9257965
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
2	55	37.2%
1	47	31.8%
3	26	17.6%
4	4	2.7%
6	3	2.0%
5	2	1.4%
10	1	0.7%
18	1	0.7%
11	1	0.7%
(Missing)	8	5.4%

Value	Count	Frequency (%)
1	47	31.8%
2	55	37.2%
3	26	17.6%
4	4	2.7%
5	2	1.4%
6	3	2.0%
10	1	0.7%
11	1	0.7%
18	1	0.7%

Value	Count	Frequency (%)
18	1	0.7%
11	1	0.7%
10	1	0.7%
6	3	2.0%
5	2	1.4%
4	4	2.7%
3	26	17.6%
2	55	37.2%
1	47	31.8%

cant_apercibimientos
Unsupported

Missing Rejected Unsupported

Missing	148
Missing (%)	100.0%
Memory size	2.3 KiB

cant_suspensiones
Categorical

Constant Missing

Distinct	1
Distinct (%)	100.0%
Missing	147
Missing (%)	99.3%
Memory size	9.3 KiB

1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	3
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	100.0%

Sample

1st row	1.0

Common Values

Value	Count	Frequency (%)
1.0	1	0.7%
(Missing)	147	99.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	1	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

cant_antecedentes
Categorical

Constant Missing

Distinct	1
Distinct (%)	100.0%
Missing	147
Missing (%)	99.3%
Memory size	9.3 KiB

1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	3
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	100.0%

Sample

1st row	1.0

Common Values

Value	Count	Frequency (%)
1.0	1	0.7%
(Missing)	147	99.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	1	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

cant_Apoderado
Real number (ℝ)

High correlation Missing

Distinct	6
Distinct (%)	5.6%
Missing	41
Missing (%)	27.7%
Infinite	0
Infinite (%)	0.0%
Mean	1.635514

Minimum	1
Maximum	6
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.3 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	2
95-th percentile	3.7
Maximum	6
Range	5
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.97509093
Coefficient of variation (CV)	0.59619846
Kurtosis	4.2194209
Mean	1.635514
Median Absolute Deviation (MAD)	0
Skewness	1.9119639
Sum	175
Variance	0.95080233
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
1	64	43.2%
2	27	18.2%
3	10	6.8%
4	4	2.7%
6	1	0.7%
5	1	0.7%
(Missing)	41	27.7%

Value	Count	Frequency (%)
1	64	43.2%
2	27	18.2%
3	10	6.8%
4	4	2.7%
5	1	0.7%
6	1	0.7%

Value	Count	Frequency (%)
6	1	0.7%
5	1	0.7%
4	4	2.7%
3	10	6.8%
2	27	18.2%
1	64	43.2%

cant_representante
Categorical

High correlation Imbalance Missing

Distinct	3
Distinct (%)	3.4%
Missing	60
Missing (%)	40.5%
Memory size	9.6 KiB

1.0	75
2.0	12
3.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	264
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.1%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	75	50.7%
2.0	12	8.1%
3.0	1	0.7%
(Missing)	60	40.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	75	85.2%
2.0	12	13.6%
3.0	1	1.1%

Most occurring characters

Value	Count	Frequency (%)
.	88	33.3%
0	88	33.3%
1	75	28.4%
2	12	4.5%
3	1	0.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	264	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	88	33.3%
0	88	33.3%
1	75	28.4%
2	12	4.5%
3	1	0.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	264	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	88	33.3%
0	88	33.3%
1	75	28.4%
2	12	4.5%
3	1	0.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	264	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	88	33.3%
0	88	33.3%
1	75	28.4%
2	12	4.5%
3	1	0.4%

cant_autenticado
Categorical

High correlation

Distinct	4
Distinct (%)	2.7%
Missing	0
Missing (%)	0.0%
Memory size	9.8 KiB

1.0	99
2.0	38
3.0	10
6.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	444
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.7%

Sample

1st row	1.0
2nd row	1.0
3rd row	6.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	99	66.9%
2.0	38	25.7%
3.0	10	6.8%
6.0	1	0.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	99	66.9%
2.0	38	25.7%
3.0	10	6.8%
6.0	1	0.7%

Most occurring characters

Value	Count	Frequency (%)
.	148	33.3%
0	148	33.3%
1	99	22.3%
2	38	8.6%
3	10	2.3%
6	1	0.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	444	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	148	33.3%
0	148	33.3%
1	99	22.3%
2	38	8.6%
3	10	2.3%
6	1	0.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	444	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	148	33.3%
0	148	33.3%
1	99	22.3%
2	38	8.6%
3	10	2.3%
6	1	0.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	444	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	148	33.3%
0	148	33.3%
1	99	22.3%
2	38	8.6%
3	10	2.3%
6	1	0.2%

cant_noAutenticado
Categorical

High correlation Missing

Distinct	4
Distinct (%)	8.7%
Missing	102
Missing (%)	68.9%
Memory size	9.4 KiB

1.0	32
2.0	9
3.0	4
4.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	138
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	2.2%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	3.0
5th row	3.0

Common Values

Value	Count	Frequency (%)
1.0	32	21.6%
2.0	9	6.1%
3.0	4	2.7%
4.0	1	0.7%
(Missing)	102	68.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	32	69.6%
2.0	9	19.6%
3.0	4	8.7%
4.0	1	2.2%

Most occurring characters

Value	Count	Frequency (%)
.	46	33.3%
0	46	33.3%
1	32	23.2%
2	9	6.5%
3	4	2.9%
4	1	0.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	138	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	46	33.3%
0	46	33.3%
1	32	23.2%
2	9	6.5%
3	4	2.9%
4	1	0.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	138	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	46	33.3%
0	46	33.3%
1	32	23.2%
2	9	6.5%
3	4	2.9%
4	1	0.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	138	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	46	33.3%
0	46	33.3%
1	32	23.2%
2	9	6.5%
3	4	2.9%
4	1	0.7%

cant_sinMontoLimite
Categorical

Missing

Distinct	4
Distinct (%)	6.3%
Missing	85
Missing (%)	57.4%
Memory size	9.5 KiB

1.0	44
2.0	13
3.0	4
4.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	189
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	2.0
5th row	4.0

Common Values

Value	Count	Frequency (%)
1.0	44	29.7%
2.0	13	8.8%
3.0	4	2.7%
4.0	2	1.4%
(Missing)	85	57.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	44	69.8%
2.0	13	20.6%
3.0	4	6.3%
4.0	2	3.2%

Most occurring characters

Value	Count	Frequency (%)
.	63	33.3%
0	63	33.3%
1	44	23.3%
2	13	6.9%
3	4	2.1%
4	2	1.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	189	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	63	33.3%
0	63	33.3%
1	44	23.3%
2	13	6.9%
3	4	2.1%
4	2	1.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	189	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	63	33.3%
0	63	33.3%
1	44	23.3%
2	13	6.9%
3	4	2.1%
4	2	1.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	189	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	63	33.3%
0	63	33.3%
1	44	23.3%
2	13	6.9%
3	4	2.1%
4	2	1.1%

cant_MontoLimite
Categorical

High correlation Imbalance

Distinct	5
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Memory size	9.8 KiB

1.0	118
2.0	25
3.0	3
6.0	1
4.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	444
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	1.4%

Sample

1st row	2.0
2nd row	1.0
3rd row	6.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	118	79.7%
2.0	25	16.9%
3.0	3	2.0%
6.0	1	0.7%
4.0	1	0.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	118	79.7%
2.0	25	16.9%
3.0	3	2.0%
6.0	1	0.7%
4.0	1	0.7%

Most occurring characters

Value	Count	Frequency (%)
.	148	33.3%
0	148	33.3%
1	118	26.6%
2	25	5.6%
3	3	0.7%
6	1	0.2%
4	1	0.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	444	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	148	33.3%
0	148	33.3%
1	118	26.6%
2	25	5.6%
3	3	0.7%
6	1	0.2%
4	1	0.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	444	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	148	33.3%
0	148	33.3%
1	118	26.6%
2	25	5.6%
3	3	0.7%
6	1	0.2%
4	1	0.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	444	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	148	33.3%
0	148	33.3%
1	118	26.6%
2	25	5.6%
3	3	0.7%
6	1	0.2%
4	1	0.2%

total_articulos_provee
Real number (ℝ)

High correlation

Distinct	67
Distinct (%)	45.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	50.304054

Minimum	1
Maximum	703
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.3 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	4
median	12
Q3	43.25
95-th percentile	204.75
Maximum	703
Range	702
Interquartile range (IQR)	39.25

Descriptive statistics

Standard deviation	101.01341
Coefficient of variation (CV)	2.0080571
Kurtosis	19.86692
Mean	50.304054
Median Absolute Deviation (MAD)	11
Skewness	4.0568562
Sum	7445
Variance	10203.71
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	19	12.8%
3	11	7.4%
7	6	4.1%
8	6	4.1%
12	6	4.1%
2	5	3.4%
6	5	3.4%
9	5	3.4%
4	4	2.7%
13	4	2.7%
Other values (57)	77	52.0%

Value	Count	Frequency (%)
1	19	12.8%
2	5	3.4%
3	11	7.4%
4	4	2.7%
5	4	2.7%
6	5	3.4%
7	6	4.1%
8	6	4.1%
9	5	3.4%
10	2	1.4%

Value	Count	Frequency (%)
703	1	0.7%
619	1	0.7%
480	1	0.7%
331	1	0.7%
327	1	0.7%
243	1	0.7%
219	1	0.7%
210	1	0.7%
195	1	0.7%
163	1	0.7%

dmonto_total_adjudicado
Categorical

Distinct	20
Distinct (%)	13.5%
Missing	0
Missing (%)	0.0%
Memory size	12.5 KiB

(377.939- 599.760]	13
(13.557.176- 19.975.532]	11
(6.702.697- 9.424.898]	11
(46.718.747- 89.439.449]	9
(222.964.579- 46.172.150.151]	9
Other values (15)	95

Length

Max length	29
Median length	24
Mean length	21.486486
Min length	12

Characters and Unicode

Total characters	3180
Distinct characters	15
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	(46.718.747- 89.439.449]
2nd row	(104.767- 224.078]
3rd row	(890.758- 1.302.657]
4th row	(13.557.176- 19.975.532]
5th row	(33.011- 104.767]

Common Values

Value	Count	Frequency (%)
(377.939- 599.760]	13	8.8%
(13.557.176- 19.975.532]	11	7.4%
(6.702.697- 9.424.898]	11	7.4%
(46.718.747- 89.439.449]	9	6.1%
(222.964.579- 46.172.150.151]	9	6.1%
(3.396.600- 4.727.330]	9	6.1%
(89.439.449- 222.964.579]	9	6.1%
(1.793.326- 2.483.085]	8	5.4%
(224.078- 377.939]	8	5.4%
(33.011- 104.767]	8	5.4%
Other values (10)	53	35.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
377.939	21	7.1%
13.557.176	19	6.4%
9.424.898	19	6.4%
89.439.449	18	6.1%
599.760	18	6.1%
222.964.579	18	6.1%
19.975.532	16	5.4%
6.702.697	16	5.4%
46.718.747	15	5.1%
3.396.600	15	5.1%
Other values (11)	121	40.9%

Most occurring characters

Value	Count	Frequency (%)
.	499	15.7%
7	313	9.8%
9	299	9.4%
3	232	7.3%
4	216	6.8%
2	186	5.8%
1	185	5.8%
6	182	5.7%
0	175	5.5%
5	164	5.2%
Other values (5)	729	22.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3180	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	499	15.7%
7	313	9.8%
9	299	9.4%
3	232	7.3%
4	216	6.8%
2	186	5.8%
1	185	5.8%
6	182	5.7%
0	175	5.5%
5	164	5.2%
Other values (5)	729	22.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3180	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	499	15.7%
7	313	9.8%
9	299	9.4%
3	232	7.3%
4	216	6.8%
2	186	5.8%
1	185	5.8%
6	182	5.7%
0	175	5.5%
5	164	5.2%
Other values (5)	729	22.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3180	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	499	15.7%
7	313	9.8%
9	299	9.4%
3	232	7.3%
4	216	6.8%
2	186	5.8%
1	185	5.8%
6	182	5.7%
0	175	5.5%
5	164	5.2%
Other values (5)	729	22.9%

dcant_procesos_adjudicado
Categorical

High correlation

Distinct	10
Distinct (%)	6.8%
Missing	0
Missing (%)	0.0%
Memory size	11.1 KiB

(0.999, 2.0]	77
(2.0, 3.0]	11
(8.0, 12.0]	11
(19.0, 39.0]	10
(5.0, 6.0]	8
Other values (5)	31

Length

Max length	14
Median length	12
Mean length	11.547297
Min length	10

Characters and Unicode

Total characters	1709
Distinct characters	14
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	(2.0, 3.0]
2nd row	(0.999, 2.0]
3rd row	(0.999, 2.0]
4th row	(19.0, 39.0]
5th row	(0.999, 2.0]

Common Values

Value	Count	Frequency (%)
(0.999, 2.0]	77	52.0%
(2.0, 3.0]	11	7.4%
(8.0, 12.0]	11	7.4%
(19.0, 39.0]	10	6.8%
(5.0, 6.0]	8	5.4%
(12.0, 19.0]	8	5.4%
(39.0, 1214.0]	7	4.7%
(3.0, 4.0]	7	4.7%
(4.0, 5.0]	5	3.4%
(6.0, 8.0]	4	2.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2.0	88	29.7%
0.999	77	26.0%
12.0	19	6.4%
3.0	18	6.1%
19.0	18	6.1%
39.0	17	5.7%
8.0	15	5.1%
5.0	13	4.4%
6.0	12	4.1%
4.0	12	4.1%

Most occurring characters

Value	Count	Frequency (%)
0	296	17.3%
.	296	17.3%
9	266	15.6%
(	148	8.7%
,	148	8.7%
	148	8.7%
]	148	8.7%
2	114	6.7%
1	51	3.0%
3	35	2.0%
Other values (4)	59	3.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1709	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	296	17.3%
.	296	17.3%
9	266	15.6%
(	148	8.7%
,	148	8.7%
	148	8.7%
]	148	8.7%
2	114	6.7%
1	51	3.0%
3	35	2.0%
Other values (4)	59	3.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1709	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	296	17.3%
.	296	17.3%
9	266	15.6%
(	148	8.7%
,	148	8.7%
	148	8.7%
]	148	8.7%
2	114	6.7%
1	51	3.0%
3	35	2.0%
Other values (4)	59	3.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1709	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	296	17.3%
.	296	17.3%
9	266	15.6%
(	148	8.7%
,	148	8.7%
	148	8.7%
]	148	8.7%
2	114	6.7%
1	51	3.0%
3	35	2.0%
Other values (4)	59	3.5%

dtotal_articulos_provee
Categorical

High correlation

Distinct	15
Distinct (%)	10.1%
Missing	0
Missing (%)	0.0%
Memory size	11.1 KiB

(0.999, 2.0]	24
(11.0, 15.0]	15
(97.6, 161.0]	14
(29.0, 40.0]	12
(6.0, 8.0]	12
Other values (10)	71

Length

Max length	15
Median length	12
Mean length	11.695946
Min length	10

Characters and Unicode

Total characters	1731
Distinct characters	15
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	(0.999, 2.0]
2nd row	(0.999, 2.0]
3rd row	(4.0, 6.0]
4th row	(58.0, 97.6]
5th row	(0.999, 2.0]

Common Values

Value	Count	Frequency (%)
(0.999, 2.0]	24	16.2%
(11.0, 15.0]	15	10.1%
(97.6, 161.0]	14	9.5%
(29.0, 40.0]	12	8.1%
(6.0, 8.0]	12	8.1%
(2.0, 3.0]	11	7.4%
(8.0, 11.0]	10	6.8%
(4.0, 6.0]	9	6.1%
(58.0, 97.6]	8	5.4%
(21.0, 29.0]	7	4.7%
Other values (5)	26	17.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2.0	35	11.8%
11.0	25	8.4%
0.999	24	8.1%
97.6	22	7.4%
8.0	22	7.4%
15.0	21	7.1%
6.0	21	7.1%
161.0	21	7.1%
29.0	19	6.4%
40.0	18	6.1%
Other values (6)	68	23.0%

Most occurring characters

Value	Count	Frequency (%)
.	296	17.1%
0	292	16.9%
(	148	8.5%
,	148	8.5%
	148	8.5%
]	148	8.5%
1	126	7.3%
9	119	6.9%
2	67	3.9%
6	67	3.9%
Other values (5)	172	9.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1731	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	296	17.1%
0	292	16.9%
(	148	8.5%
,	148	8.5%
	148	8.5%
]	148	8.5%
1	126	7.3%
9	119	6.9%
2	67	3.9%
6	67	3.9%
Other values (5)	172	9.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1731	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	296	17.1%
0	292	16.9%
(	148	8.5%
,	148	8.5%
	148	8.5%
]	148	8.5%
1	126	7.3%
9	119	6.9%
2	67	3.9%
6	67	3.9%
Other values (5)	172	9.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1731	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	296	17.1%
0	292	16.9%
(	148	8.5%
,	148	8.5%
	148	8.5%
]	148	8.5%
1	126	7.3%
9	119	6.9%
2	67	3.9%
6	67	3.9%
Other values (5)	172	9.9%

Cluster_6
Categorical

Constant

Distinct	1
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	9.5 KiB

4	148

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	148
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4
2nd row	4
3rd row	4
4th row	4
5th row	4

Common Values

Value	Count	Frequency (%)
4	148	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
4	148	100.0%

Most occurring characters

Value	Count	Frequency (%)
4	148	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	148	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
4	148	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	148	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
4	148	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	148	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
4	148	100.0%

Interactions

Correlations

	Estado	TipoSocietario	anio_preinscripcion	antiguedad	cant_Apoderado	cant_MontoLimite	cant_autenticado	cant_noAutenticado	cant_procesos_adjudicado	cant_representante	cant_sinMontoLimite	cant_socios	dcant_procesos_adjudicado	dmonto_total_adjudicado	dtotal_articulos_provee	monto_total_adjudicado	periodo_preinscripcion	provincia	total_articulos_provee
Estado	1.000	0.262	0.142	0.126	0.000	0.000	0.072	0.000	0.000	0.082	0.000	0.000	0.000	0.060	0.042	0.000	0.142	0.000	0.000
TipoSocietario	0.262	1.000	0.198	0.215	0.079	0.000	0.231	0.000	0.157	0.000	0.223	0.000	0.084	0.053	0.000	0.000	0.198	0.385	0.000
anio_preinscripcion	0.142	0.198	1.000	-1.000	-0.084	0.000	0.000	0.000	-0.298	0.000	0.000	-0.099	0.000	0.000	0.074	-0.200	0.914	0.262	-0.093
antiguedad	0.126	0.215	-1.000	1.000	0.084	0.000	0.000	0.000	0.298	0.000	0.000	0.101	0.000	0.000	0.050	0.199	-0.914	0.203	0.093
cant_Apoderado	0.000	0.079	-0.084	0.084	1.000	0.728	0.641	0.678	0.184	0.000	0.483	0.265	0.000	0.269	0.223	0.297	-0.041	0.000	0.161
cant_MontoLimite	0.000	0.000	0.000	0.000	0.728	1.000	0.602	0.564	0.000	0.192	0.000	0.498	0.000	0.193	0.140	0.068	0.000	0.000	0.000
cant_autenticado	0.072	0.231	0.000	0.000	0.641	0.602	1.000	0.053	0.058	0.000	0.170	0.075	0.041	0.150	0.170	0.130	0.000	0.000	0.000
cant_noAutenticado	0.000	0.000	0.000	0.000	0.678	0.564	0.053	1.000	0.000	0.332	0.483	0.547	0.000	0.000	0.000	0.365	0.000	0.000	0.000
cant_procesos_adjudicado	0.000	0.157	-0.298	0.298	0.184	0.000	0.058	0.000	1.000	0.260	0.155	0.034	0.554	0.000	0.094	0.622	-0.339	0.000	0.326
cant_representante	0.082	0.000	0.000	0.000	0.000	0.192	0.000	0.332	0.260	1.000	0.000	0.000	0.207	0.000	0.000	0.695	0.000	0.000	0.116
cant_sinMontoLimite	0.000	0.223	0.000	0.000	0.483	0.000	0.170	0.483	0.155	0.000	1.000	0.000	0.092	0.000	0.363	0.357	0.000	0.000	0.000
cant_socios	0.000	0.000	-0.099	0.101	0.265	0.498	0.075	0.547	0.034	0.000	0.000	1.000	0.097	0.037	0.133	0.143	-0.103	0.000	-0.002
dcant_procesos_adjudicado	0.000	0.084	0.000	0.000	0.000	0.000	0.041	0.000	0.554	0.207	0.092	0.097	1.000	0.192	0.000	0.261	0.000	0.000	0.160
dmonto_total_adjudicado	0.060	0.053	0.000	0.000	0.269	0.193	0.150	0.000	0.000	0.000	0.000	0.037	0.192	1.000	0.134	0.352	0.000	0.189	0.000
dtotal_articulos_provee	0.042	0.000	0.074	0.050	0.223	0.140	0.170	0.000	0.094	0.000	0.363	0.133	0.000	0.134	1.000	0.000	0.074	0.182	0.529
monto_total_adjudicado	0.000	0.000	-0.200	0.199	0.297	0.068	0.130	0.365	0.622	0.695	0.357	0.143	0.261	0.352	0.000	1.000	-0.248	0.000	0.203
periodo_preinscripcion	0.142	0.198	0.914	-0.914	-0.041	0.000	0.000	0.000	-0.339	0.000	0.000	-0.103	0.000	0.000	0.074	-0.248	1.000	0.262	-0.058
provincia	0.000	0.385	0.262	0.203	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.189	0.182	0.000	0.262	1.000	0.618
total_articulos_provee	0.000	0.000	-0.093	0.093	0.161	0.000	0.000	0.000	0.326	0.116	0.000	-0.002	0.160	0.000	0.529	0.203	-0.058	0.618	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

	CUIT	Nombre	FechaPreinscripcion	Estado	TipoSocietario	periodo_preinscripcion	anio_preinscripcion	cant_procesos_adjudicado	monto_total_adjudicado	antiguedad	provincia	cant_socios	cant_apercibimientos	cant_suspensiones	cant_antecedentes	cant_Apoderado	cant_representante	cant_autenticado	cant_noAutenticado	cant_sinMontoLimite	cant_MontoLimite	total_articulos_provee	dmonto_total_adjudicado	dcant_procesos_adjudicado	dtotal_articulos_provee	Cluster_6
201	30558766987	EDITORIAL ALBATROS	15/11/2016	Inscripto	Sociedad Anónima	201611	2016	3.0	4.751420e+07	5.0	CABA	3.0	NaN	NaN	NaN	1.0	1.0	1.0	1.0	NaN	2.0	1.0	(46.718.747- 89.439.449]	(2.0, 3.0]	(0.999, 2.0]	4
204	30715168800	construir futuros	26/07/2016	Desactualizado doc. vencidos	Sociedades De Hecho	201607	2016	2.0	1.395152e+05	5.0	Buenos Aires	1.0	NaN	NaN	NaN	1.0	NaN	1.0	NaN	NaN	1.0	1.0	(104.767- 224.078]	(0.999, 2.0]	(0.999, 2.0]	4
335	30664177818	FUNDACION DE LA UNIVERSIDAD NACIONAL DEL SUR	13/06/2017	Desactualizado doc. vencidos	Otras Formas Societarias	201706	2017	2.0	8.973327e+05	4.0	Buenos Aires	1.0	NaN	NaN	NaN	6.0	1.0	6.0	1.0	1.0	6.0	6.0	(890.758- 1.302.657]	(0.999, 2.0]	(4.0, 6.0]	4
382	30620477113	MULTICABLE S.A.	12/01/2017	Inscripto	Sociedad Anónima	201701	2017	28.0	1.371836e+07	4.0	CABA	1.0	NaN	NaN	NaN	1.0	NaN	1.0	NaN	NaN	1.0	70.0	(13.557.176- 19.975.532]	(19.0, 39.0]	(58.0, 97.6]	4
386	30629086524	AD-HOC S.R.L.	21/06/2017	Desactualizado doc. vencidos	S.R.L	201706	2017	1.0	4.370700e+04	4.0	CABA	1.0	NaN	NaN	NaN	1.0	1.0	1.0	1.0	1.0	1.0	1.0	(33.011- 104.767]	(0.999, 2.0]	(0.999, 2.0]	4
415	33708630409	ITSG SRL	14/11/2016	Inscripto	S.R.L	201611	2016	22.0	1.295317e+08	5.0	CABA	1.0	NaN	NaN	NaN	1.0	NaN	1.0	NaN	NaN	1.0	151.0	(89.439.449- 222.964.579]	(19.0, 39.0]	(97.6, 161.0]	4
423	30525366657	Refinitiv Ltd	03/01/2017	Inscripto	Otras Formas Societarias	201701	2017	17.0	9.995957e+06	4.0	CABA	1.0	NaN	NaN	NaN	2.0	NaN	2.0	NaN	1.0	1.0	3.0	(9.424.898- 13.557.176]	(12.0, 19.0]	(2.0, 3.0]	4
458	30505725774	FUNDARG S.R.L	07/07/2017	Inscripto	S.R.L	201707	2017	4.0	4.155352e+06	4.0	Córdoba	2.0	NaN	NaN	NaN	1.0	1.0	2.0	NaN	NaN	2.0	7.0	(3.396.600- 4.727.330]	(3.0, 4.0]	(6.0, 8.0]	4
602	30710910916	Cooperativa de Trabajo Dario Santillan Limitada	08/11/2016	Inscripto	Cooperativas	201611	2016	17.0	1.532279e+08	5.0	CABA	3.0	NaN	NaN	NaN	1.0	NaN	1.0	NaN	NaN	1.0	114.0	(89.439.449- 222.964.579]	(12.0, 19.0]	(97.6, 161.0]	4
747	30696184263	MB-GEOAIR SA	03/05/2017	Inscripto	Sociedad Anónima	201705	2017	1.0	1.135621e+06	4.0	CABA	2.0	NaN	NaN	NaN	1.0	NaN	1.0	NaN	NaN	1.0	49.0	(890.758- 1.302.657]	(0.999, 2.0]	(40.0, 58.0]	4

	CUIT	Nombre	FechaPreinscripcion	Estado	TipoSocietario	periodo_preinscripcion	anio_preinscripcion	cant_procesos_adjudicado	monto_total_adjudicado	antiguedad	provincia	cant_socios	cant_apercibimientos	cant_suspensiones	cant_antecedentes	cant_Apoderado	cant_representante	cant_autenticado	cant_noAutenticado	cant_sinMontoLimite	cant_MontoLimite	total_articulos_provee	dmonto_total_adjudicado	dcant_procesos_adjudicado	dtotal_articulos_provee	Cluster_6
8820	30715853465	PRODUCCIONES LA MAQUINA S.R.L.	18/04/2018	Inscripto	S.R.L	201804	2018	2.0	1.571110e+07	3.0	CABA	2.0	NaN	NaN	NaN	1.0	1.0	1.0	1.0	1.0	1.0	12.0	(13.557.176- 19.975.532]	(0.999, 2.0]	(11.0, 15.0]	4
8853	30714777439	ANGEL BOHORQUEZ y DEL HIERRO ROBERTO SH	11/07/2019	Inscripto	Sociedades De Hecho	201907	2019	1.0	6.425723e+06	2.0	Buenos Aires	2.0	NaN	NaN	NaN	2.0	NaN	2.0	NaN	NaN	2.0	11.0	(4.727.330- 6.702.697]	(0.999, 2.0]	(8.0, 11.0]	4
9415	30638733427	ALDO BOLZAN Y HNOS SRL	18/04/2017	Inscripto	S.R.L	201704	2017	1.0	6.763057e+05	4.0	Córdoba	2.0	NaN	NaN	NaN	NaN	2.0	1.0	1.0	NaN	2.0	26.0	(599.760- 890.758]	(0.999, 2.0]	(21.0, 29.0]	4
9571	30711460418	PATAGONIA STEEL S.R.L.	07/09/2021	Inscripto	S.R.L	202109	2021	1.0	8.137786e+05	0.0	Chubut	1.0	NaN	NaN	NaN	NaN	1.0	1.0	NaN	NaN	1.0	219.0	(599.760- 890.758]	(0.999, 2.0]	(161.0, 345.0]	4
9591	30709902527	CASEROS PARK S.A.	24/11/2016	Inscripto	Sociedad Anónima	201611	2016	1.0	2.880000e+07	5.0	CABA	3.0	NaN	NaN	NaN	1.0	NaN	1.0	NaN	NaN	1.0	1.0	(19.975.532- 30.451.916]	(0.999, 2.0]	(0.999, 2.0]	4
9693	30716844583	GRUPO WG S.A.S	20/04/2022	Inscripto	Otras Formas Societarias	202204	2022	2.0	2.508003e+05	0.0	Corrientes	2.0	NaN	NaN	NaN	NaN	1.0	1.0	NaN	NaN	1.0	703.0	(224.078- 377.939]	(0.999, 2.0]	(345.0, 6993.0]	4
9831	30716327279	Diversitas S.R.L.	09/05/2022	Inscripto	S.R.L	202205	2022	1.0	4.050000e+05	0.0	CABA	2.0	NaN	NaN	NaN	NaN	1.0	1.0	NaN	NaN	1.0	24.0	(377.939- 599.760]	(0.999, 2.0]	(21.0, 29.0]	4
9907	30700951738	MVS SA	15/03/2022	Inscripto	Sociedad Anónima	202203	2022	1.0	4.371429e+06	0.0	CABA	2.0	NaN	NaN	NaN	2.0	NaN	1.0	1.0	NaN	2.0	4.0	(3.396.600- 4.727.330]	(0.999, 2.0]	(3.0, 4.0]	4
9971	30712369120	PINTURERIA ARGENTINA SH	24/06/2022	Inscripto	Sociedades De Hecho	202206	2022	1.0	4.614677e+04	0.0	Rio Negro	3.0	NaN	NaN	NaN	NaN	1.0	1.0	NaN	NaN	1.0	33.0	(33.011- 104.767]	(0.999, 2.0]	(29.0, 40.0]	4
10073	30700503891	GIJON SA	07/09/2022	Inscripto	Sociedad Anónima	202209	2022	1.0	1.119596e+07	0.0	CABA	3.0	NaN	NaN	NaN	1.0	NaN	1.0	NaN	NaN	1.0	1.0	(9.424.898- 13.557.176]	(0.999, 2.0]	(0.999, 2.0]	4

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)